How satellite rainfall estimate errors may impact rainfed cereal yield simulation in West Africa
Rainfall monitoring via satellite sensors is particularly relevant for the agricultural sector of West Africa. Indeed, food shortages in this region are often caused by rainfall deficits and an early access to data available for the entire region can help to provide credible and timely information for better decision making. This study assesses the accuracy of state-of-the-art satellite rainfall retrievals for agriculture applications in two sites in Niger and Benin. Although these satellite data are widely used instead of rain gauge data for such applications, we found that, in a crop-modelling framework, their use can introduce large biases in crop yield simulations. Biases differ strongly among the four cultivars considered in both sites and are not simple extrapolation of each satellite product cumulative rainfall amount biases. In particular, we found that if an accurate estimation of the annual cumulative rainfall amount is important for yield simulations of pearl millet 'Souna 3' and 'Somno' cultivars in Niger, a realistic distribution of rainfall is also very important for predicting pearl millet 'Somno' and 'HK' yields in Niger as well as maize yields in Benin. Overall the satellite products tested, 3B42v6 appears to be the most suitable satellite product for our specific agricultural application since it minimizes both biases in rainfall distribution and in annual cumulative rainfall amount. For each crop and in both regions, biases in crop yield prediction are the highest when using non-calibrated satellite rainfall products (PERSIANN, 3B42RT, CMORPH and GSMAP).
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dig-cirad-fr-5697442024-01-28T21:31:10Z http://agritrop.cirad.fr/569744/ http://agritrop.cirad.fr/569744/ How satellite rainfall estimate errors may impact rainfed cereal yield simulation in West Africa. Ramarohetra Johanna, Sultan Benjamin, Baron Christian, Gaiser Thomas, Gosset Marielle. 2013. Agricultural and Forest Meteorology, 180 : 118-131.https://doi.org/10.1016/j.agrformet.2013.05.010 <https://doi.org/10.1016/j.agrformet.2013.05.010> How satellite rainfall estimate errors may impact rainfed cereal yield simulation in West Africa Ramarohetra, Johanna Sultan, Benjamin Baron, Christian Gaiser, Thomas Gosset, Marielle eng 2013 Agricultural and Forest Meteorology P40 - Météorologie et climatologie F01 - Culture des plantes U30 - Méthodes de recherche U10 - Informatique, mathématiques et statistiques précipitation télédétection modèle de simulation méthodologie rendement des cultures plante céréalière Cenchrus americanus zone agroclimatique facteur climatique imagerie par satellite http://aims.fao.org/aos/agrovoc/c_6161 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_12522 http://aims.fao.org/aos/agrovoc/c_10176 http://aims.fao.org/aos/agrovoc/c_25512 http://aims.fao.org/aos/agrovoc/c_13199 http://aims.fao.org/aos/agrovoc/c_28638 http://aims.fao.org/aos/agrovoc/c_29554 http://aims.fao.org/aos/agrovoc/c_36761 Bénin Niger Afrique occidentale Sahel http://aims.fao.org/aos/agrovoc/c_875 http://aims.fao.org/aos/agrovoc/c_5181 http://aims.fao.org/aos/agrovoc/c_8355 http://aims.fao.org/aos/agrovoc/c_6734 Rainfall monitoring via satellite sensors is particularly relevant for the agricultural sector of West Africa. Indeed, food shortages in this region are often caused by rainfall deficits and an early access to data available for the entire region can help to provide credible and timely information for better decision making. This study assesses the accuracy of state-of-the-art satellite rainfall retrievals for agriculture applications in two sites in Niger and Benin. Although these satellite data are widely used instead of rain gauge data for such applications, we found that, in a crop-modelling framework, their use can introduce large biases in crop yield simulations. Biases differ strongly among the four cultivars considered in both sites and are not simple extrapolation of each satellite product cumulative rainfall amount biases. In particular, we found that if an accurate estimation of the annual cumulative rainfall amount is important for yield simulations of pearl millet 'Souna 3' and 'Somno' cultivars in Niger, a realistic distribution of rainfall is also very important for predicting pearl millet 'Somno' and 'HK' yields in Niger as well as maize yields in Benin. Overall the satellite products tested, 3B42v6 appears to be the most suitable satellite product for our specific agricultural application since it minimizes both biases in rainfall distribution and in annual cumulative rainfall amount. For each crop and in both regions, biases in crop yield prediction are the highest when using non-calibrated satellite rainfall products (PERSIANN, 3B42RT, CMORPH and GSMAP). article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/569744/1/document_569744.pdf application/pdf Cirad license info:eu-repo/semantics/restrictedAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.1016/j.agrformet.2013.05.010 10.1016/j.agrformet.2013.05.010 info:eu-repo/semantics/altIdentifier/doi/10.1016/j.agrformet.2013.05.010 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.1016/j.agrformet.2013.05.010 |
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P40 - Météorologie et climatologie F01 - Culture des plantes U30 - Méthodes de recherche U10 - Informatique, mathématiques et statistiques précipitation télédétection modèle de simulation méthodologie rendement des cultures plante céréalière Cenchrus americanus zone agroclimatique facteur climatique imagerie par satellite http://aims.fao.org/aos/agrovoc/c_6161 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_12522 http://aims.fao.org/aos/agrovoc/c_10176 http://aims.fao.org/aos/agrovoc/c_25512 http://aims.fao.org/aos/agrovoc/c_13199 http://aims.fao.org/aos/agrovoc/c_28638 http://aims.fao.org/aos/agrovoc/c_29554 http://aims.fao.org/aos/agrovoc/c_36761 http://aims.fao.org/aos/agrovoc/c_875 http://aims.fao.org/aos/agrovoc/c_5181 http://aims.fao.org/aos/agrovoc/c_8355 http://aims.fao.org/aos/agrovoc/c_6734 P40 - Météorologie et climatologie F01 - Culture des plantes U30 - Méthodes de recherche U10 - Informatique, mathématiques et statistiques précipitation télédétection modèle de simulation méthodologie rendement des cultures plante céréalière Cenchrus americanus zone agroclimatique facteur climatique imagerie par satellite http://aims.fao.org/aos/agrovoc/c_6161 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_12522 http://aims.fao.org/aos/agrovoc/c_10176 http://aims.fao.org/aos/agrovoc/c_25512 http://aims.fao.org/aos/agrovoc/c_13199 http://aims.fao.org/aos/agrovoc/c_28638 http://aims.fao.org/aos/agrovoc/c_29554 http://aims.fao.org/aos/agrovoc/c_36761 http://aims.fao.org/aos/agrovoc/c_875 http://aims.fao.org/aos/agrovoc/c_5181 http://aims.fao.org/aos/agrovoc/c_8355 http://aims.fao.org/aos/agrovoc/c_6734 |
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P40 - Météorologie et climatologie F01 - Culture des plantes U30 - Méthodes de recherche U10 - Informatique, mathématiques et statistiques précipitation télédétection modèle de simulation méthodologie rendement des cultures plante céréalière Cenchrus americanus zone agroclimatique facteur climatique imagerie par satellite http://aims.fao.org/aos/agrovoc/c_6161 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_12522 http://aims.fao.org/aos/agrovoc/c_10176 http://aims.fao.org/aos/agrovoc/c_25512 http://aims.fao.org/aos/agrovoc/c_13199 http://aims.fao.org/aos/agrovoc/c_28638 http://aims.fao.org/aos/agrovoc/c_29554 http://aims.fao.org/aos/agrovoc/c_36761 http://aims.fao.org/aos/agrovoc/c_875 http://aims.fao.org/aos/agrovoc/c_5181 http://aims.fao.org/aos/agrovoc/c_8355 http://aims.fao.org/aos/agrovoc/c_6734 P40 - Météorologie et climatologie F01 - Culture des plantes U30 - Méthodes de recherche U10 - Informatique, mathématiques et statistiques précipitation télédétection modèle de simulation méthodologie rendement des cultures plante céréalière Cenchrus americanus zone agroclimatique facteur climatique imagerie par satellite http://aims.fao.org/aos/agrovoc/c_6161 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_12522 http://aims.fao.org/aos/agrovoc/c_10176 http://aims.fao.org/aos/agrovoc/c_25512 http://aims.fao.org/aos/agrovoc/c_13199 http://aims.fao.org/aos/agrovoc/c_28638 http://aims.fao.org/aos/agrovoc/c_29554 http://aims.fao.org/aos/agrovoc/c_36761 http://aims.fao.org/aos/agrovoc/c_875 http://aims.fao.org/aos/agrovoc/c_5181 http://aims.fao.org/aos/agrovoc/c_8355 http://aims.fao.org/aos/agrovoc/c_6734 Ramarohetra, Johanna Sultan, Benjamin Baron, Christian Gaiser, Thomas Gosset, Marielle How satellite rainfall estimate errors may impact rainfed cereal yield simulation in West Africa |
description |
Rainfall monitoring via satellite sensors is particularly relevant for the agricultural sector of West Africa. Indeed, food shortages in this region are often caused by rainfall deficits and an early access to data available for the entire region can help to provide credible and timely information for better decision making. This study assesses the accuracy of state-of-the-art satellite rainfall retrievals for agriculture applications in two sites in Niger and Benin. Although these satellite data are widely used instead of rain gauge data for such applications, we found that, in a crop-modelling framework, their use can introduce large biases in crop yield simulations. Biases differ strongly among the four cultivars considered in both sites and are not simple extrapolation of each satellite product cumulative rainfall amount biases. In particular, we found that if an accurate estimation of the annual cumulative rainfall amount is important for yield simulations of pearl millet 'Souna 3' and 'Somno' cultivars in Niger, a realistic distribution of rainfall is also very important for predicting pearl millet 'Somno' and 'HK' yields in Niger as well as maize yields in Benin. Overall the satellite products tested, 3B42v6 appears to be the most suitable satellite product for our specific agricultural application since it minimizes both biases in rainfall distribution and in annual cumulative rainfall amount. For each crop and in both regions, biases in crop yield prediction are the highest when using non-calibrated satellite rainfall products (PERSIANN, 3B42RT, CMORPH and GSMAP). |
format |
article |
topic_facet |
P40 - Météorologie et climatologie F01 - Culture des plantes U30 - Méthodes de recherche U10 - Informatique, mathématiques et statistiques précipitation télédétection modèle de simulation méthodologie rendement des cultures plante céréalière Cenchrus americanus zone agroclimatique facteur climatique imagerie par satellite http://aims.fao.org/aos/agrovoc/c_6161 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_24242 http://aims.fao.org/aos/agrovoc/c_12522 http://aims.fao.org/aos/agrovoc/c_10176 http://aims.fao.org/aos/agrovoc/c_25512 http://aims.fao.org/aos/agrovoc/c_13199 http://aims.fao.org/aos/agrovoc/c_28638 http://aims.fao.org/aos/agrovoc/c_29554 http://aims.fao.org/aos/agrovoc/c_36761 http://aims.fao.org/aos/agrovoc/c_875 http://aims.fao.org/aos/agrovoc/c_5181 http://aims.fao.org/aos/agrovoc/c_8355 http://aims.fao.org/aos/agrovoc/c_6734 |
author |
Ramarohetra, Johanna Sultan, Benjamin Baron, Christian Gaiser, Thomas Gosset, Marielle |
author_facet |
Ramarohetra, Johanna Sultan, Benjamin Baron, Christian Gaiser, Thomas Gosset, Marielle |
author_sort |
Ramarohetra, Johanna |
title |
How satellite rainfall estimate errors may impact rainfed cereal yield simulation in West Africa |
title_short |
How satellite rainfall estimate errors may impact rainfed cereal yield simulation in West Africa |
title_full |
How satellite rainfall estimate errors may impact rainfed cereal yield simulation in West Africa |
title_fullStr |
How satellite rainfall estimate errors may impact rainfed cereal yield simulation in West Africa |
title_full_unstemmed |
How satellite rainfall estimate errors may impact rainfed cereal yield simulation in West Africa |
title_sort |
how satellite rainfall estimate errors may impact rainfed cereal yield simulation in west africa |
url |
http://agritrop.cirad.fr/569744/ http://agritrop.cirad.fr/569744/1/document_569744.pdf |
work_keys_str_mv |
AT ramarohetrajohanna howsatelliterainfallestimateerrorsmayimpactrainfedcerealyieldsimulationinwestafrica AT sultanbenjamin howsatelliterainfallestimateerrorsmayimpactrainfedcerealyieldsimulationinwestafrica AT baronchristian howsatelliterainfallestimateerrorsmayimpactrainfedcerealyieldsimulationinwestafrica AT gaiserthomas howsatelliterainfallestimateerrorsmayimpactrainfedcerealyieldsimulationinwestafrica AT gossetmarielle howsatelliterainfallestimateerrorsmayimpactrainfedcerealyieldsimulationinwestafrica |
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1792498491136671744 |